From 875d3d0ace10f766331679daac2c26b28f203899 Mon Sep 17 00:00:00 2001
From: Tiago Freitas Pereira <tiagofrepereira@gmail.com>
Date: Wed, 18 Feb 2015 10:02:02 +0100
Subject: [PATCH] Documenting

---
 doc/guide.rst | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/doc/guide.rst b/doc/guide.rst
index cfb2d76..635791d 100644
--- a/doc/guide.rst
+++ b/doc/guide.rst
@@ -382,7 +382,7 @@ For example, to train a K-Means with 10 iterations you can use the following ste
 
 
 With that granularity you can train your K-Means (or any trainer procedure) with your own convergence criteria.
-Furthermore, to make the things even simpler, it is possible to train the K-Means (and have the same example as above) using the wrapper :py:method:`bob.learn.em.train` as in the example below:
+Furthermore, to make the things even simpler, it is possible to train the K-Means (and have the same example as above) using the wrapper :py:class:`bob.learn.em.train` as in the example below:
 
 .. doctest::
    :options: +NORMALIZE_WHITESPACE
-- 
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